The Hospital Microbiome Project: Experimental Designs for Investigating the Development of Microbial Communities

Daniel Patrick Smith

Hospital Microbiome WorkshopUniversity of Chicago, 1.15.2013

Background

How microbial communities persist and change in indoor environments is of immense interest to public health bodies and scientists.

Demographics of a building play a key role in shaping microbial communities. – Humans aerosolize up to 37

million bacteria per person-hour (Qian, 2012)

– Forensic microbiology can determine who last touched an object by their microbiota. (Fierer, 2010)

Qian, J., Hospodsky, D., Yamamoto, N., Nazaroff, W. W. & Peccia, J. Indoor Air (2012).Fisk, W. J. Annual Review of Energy and the Environment 25, 537–566 (2000).Fierer, N. et al. Proceedings of the National Academy of Sciences 107, 6477–6481 (2010).

Hospital Microbiome Workshop

Background:Hospitals as a Sampling Site

A newly constructed hospital presents the ideal conditions for studying the development of bacterial communities driven by human demographics.

– Patient rooms are identically constructed – replicates.

– Building materials are defined.– Closed environment.– No prior pathogenic contamination.– Relevant microorganisms are

thoroughly characterized.

Groseclose SL, et al. (2004) MMWR Morb Mortal Wkly Rep 51: 1–84.Hall-Baker PA, et al. (2010) MMWR Morb Mortal Wkly Rep 57: 1–100.

Background:Hospital vs. Non-Hospital Infections

Contracted Fatal (% Fatal)Hospital 1.7 million 99,000 (6%)Non-Hospital 1.5 million 15,743 (1%)

Cause of Death – Total over U.S. in 2002 Number1. Diseases of heart 696,9472. Malignant neoplasms 557,2713. Cerebrovascular diseases 162,6724. Chronic lower respiratory diseases 124,8165. Accidents (unintentional injuries) 106,742

Hospital Acquired Infection - associated 99,0006. Diabetes mellitus 73,2497. Influenza and pneumonia 65,6818. Alzheimer’s disease 58,866

4.5 Infections per100 Hospital admissions

Anderson RN, Smith BL (2005) Natl Vital Stat Rep 53: 1–89.Klevens RM, et al. (2007) Public Health Rep 122: 160–166.

Background:Hospital Acquired Infections (HAI)

The ten most common pathogens:– coagulase-negative staphylococci– Staphylococcus aureus– Enterococcus species– Candida species– Escherichia coli– Pseudomonas aeruginosa– Klebsiella pneumoniae– Enterobacter species– Acinetobacter baumannii– Klebsiella oxytoca

Hidron, A. I. et al. Infection Control and Hospital Epidemiology 29, 996–1011 (2008).

Accounted for 84% of the observed HAIs in 463 hospitals over a 21 month period. (Hidron, 2008)

Project Goal

Determine which environmental parameters have the greatest influence on the development of microbial communities within a hospital.

Understand how demographics interact with the succession of microorganisms in a hospital.

Hospital Microbiome Workshop

– Patient/Staff Microflora– Building Material– Temperature/Humidity– Airflow rate– Cleaning practices

– Light Level/Source– Demographic Exposure

• High vs Low Traffic• Staff vs Patient Area

– Prior Room Occupants

Guiding Hypotheses

1. Microbial community structure on hospital surfaces can be predicted by human demographics, physical conditions (e.g. humidity, temperature), and building materials for each location and time.

2. A patient-room microbiota is influenced by the current patient and their duration of occupancy, and shows community succession with the introduction of a new occupant.

3. The colonization of the surfaces and patients by potential pathogens is influenced by composition and diversity of the existing microbial community derived from previous occupants of the space.

4. The rate of microbial succession is driven by demographic usage and building materials.

Hospital Microbiome Workshop

Hospital Microbiome Workshop

Ideal Sampling Strategy:Daily Sampling of Bacterial Reservoirs for a Year.Patient AreaBed rails, tray table, call boxes, telephone, bedside tables, patient chair, IV pole, floor, light switches, air exhaust.

Patient RestroomSink, light switches, door knob, handrails, toilet seats, flush lever, bed pan cleaning equipment, floor.

Additional EquipmentIV Pump control panel, monitor control panel, monitor touch screen, monitor cables, ventilator control panel.

WaterCold tap water, hot tap water, water used to clean floors.

PatientStool sample, nasal swab, hand.

StaffNasal swab, bottom of shoe, dominant hand, cell phone, computer mouse, work phone, shirt cuff, stethoscope.

Travel AreasCorridor floor & wall, stairwell handrail & steps & door knobs & kick plates, elevator buttons & floor & handrail.

LobbyFront desk surface, chairs, coffee tables, floor.

Public RestroomFloor, door handles, sink controls, sink bowl, soap dispenser, towel dispenser, toilet seats, toilet lever, stall door lock, stall door handle, urinal flush lever.

240 Patient Rooms + 50 Staff= 2,437,105 samples= $24 million in extraction & sequencing consumables alone

Hospital Microbiome Workshop

Implemented Sampling Strategy:Daily/Weekly Sampling for a Year of 142 Sites

Human Patients (≤ 10)

– Nose– Hand– Inguinal Fold

Staff (x8)– Nose– Hand– Uniform cuff– Pager– Cell phone– Shoe

Patient Room (x10) Floor Bedrail Cold tap water Glove box Air exhaust filter

Nurse Station (x2) Countertop Computer mouse Phone handle Chair Corridor floor Hot tap water Cold tap water

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Sampling Airborne Microorganisms

Each patient room has independent exhaust vents which can be fitted with removable filters for this study.– Sterilize filter media with autoclaving and UV-exposure– Replace filters daily/weekly.– Use ventilation rate, filter efficiency, and microbial abundance to

calculate the concentration of airborne microorganisms.

Hospital Microbiome Workshop

Sampling Protocol:Compatible with Quantitative Analyses

Sterile swabs moistened with saline solution will be used to sample a region of pre-defined dimensions.– qRT-PCR provides an estimate of genomes, yielding cells/cm2

– Allows conclusions to be drawn regarding actual abundance of microbial taxa, rather than relative abundance.

Hot and cold water supplies– Sample hot & cold water at nurse

stations on 9th & 10th floors– Patient room cold tap– Run for 15 sec– Absorb onto swab

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Sample Selection

Ten patient rooms and their occupants will be sampled– Two rooms: Sample every day.– Eight additional rooms: Sample weekly.

Addresses the hypothesis:The colonization of the surfaces and patients by potential pathogens is influenced by composition and diversity of the existing microbial community derived from previous occupants of the space.

Hospital Microbiome Workshop

Antibiotic Effects on Patient Microflora

Antibiotics dramatically alter the natural microflora of humans. We will be able to monitor the effect of several antibiotic regimens on the skin, nasal, and inguinal fold microbiomes of the subjects in this study.

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Project Timeline

January 2013– Identify all sampling locations in the building– Begin collecting surface, air, and water samples.– Secure and activate data loggers in patient rooms.

February 2013– Identify staff members who wish to participate and begin sampling

them in their current working environment. February 23rd, 2013 – Hospital Opens

– Identify patients who wish to participate and begin sampling them a they are admitted to the rooms under observation.

January 2014– Conduct chart reviews after completion of sample collection phase.

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Sample Processing

Swab tips are cut off and placed in a lysis/PCR solution.

After incubation and thorough mixing, aliquots are distributed to 96-well PCR plates in triplicate.

Amplification of 16S/18S/ITS takes place in a qualitative real time (qRT) PCR machine using barcoded primers.

Samples are pooled into groups of 500 and sequenced to a depth of 3,000 read pairs (2 x 150 bp) per sample.

Reads are filtered for quality, merged into 250 bp reads, and demultiplexed based on barcode.

Data Analysis

The QIIME software suite will be used to:– Cluster reads into operational taxonomic units (OTUs).– Phylogenetically classify OTUs based on reference databases.– Calculate alpha and beta diversity among samples.– Visualize sample similarity via principle coordinate analysis plots.

Caporaso, J. G. et al. Nature Methods 7, 335-336 (2010).

Data Analysis

SourceTracker will be used to:– Identify sources and proportions of contamination on surfaces.– Answer questions such as “What proportion of the air’s microbes

originate from a patient’s nasal microbiome?”

Knights, D. et al. Nature Methods 8, 761-763 (2011).

Data Analysis

Microbial Assemblage Prediction (MAP) will be used to:– Predict the relative abundance of microorganisms in an

environment, given set of environmental conditions.– Simulate how community composition will shift if an environmental

variable is altered.

Larsen, P. E., Field, D. & Gilbert, J. A. Nature Methods (2012).

Env. Parameter

Rhodobacteriales

Flavobacteriales

Rickettsiales

Pseudomonadales

Opitutales

Vibrionales

Rhizobiales

Data Analysis

Local Similarity Analysis will be used to:– Identify patterns in microbial succession. E.g. if organism A is

blooming now, then organism B will bloom in a few weeks.

Gilbert, J. A. et al. The ISME Journal 6, 298-308 (2011).